Constraining globular cluster formation through studies of young massive clusters - V. ALMA observations of clusters in the Antennae

Some formation scenarios that have been put forward to explain multiple populations within Globular Clusters (GCs) require that the young massive cluster have large reservoirs of cold gas within them, which is necessary to form future generations of stars. In this paper we use deep observations taken with Atacama Large Millimeter/sub-millimeter Array (ALMA) to assess the amount of molecular gas within 3 young (50-200 Myr) massive (~10^6 Msun) clusters in the Antennae galaxies. No significant CO(3--2) emission was found associated with any of the three clusters. We place upper limits for the molecular gas within these clusters of ~1x10^5 Msun (or <9 % of the current stellar mass). We briefly review different scenarios that propose multiple episodes of star formation and discuss some of their assumptions and implications. Our results are in tension with the predictions of GC formation scenarios that expect large reservoirs of cool gas within young massive clusters at these ages

Collaborative Research and Development of a Novel, Patient-Centered Digital Platform (MyEyeSite) for Rare Inherited Retinal Disease Data: Acceptability and Feasibility Study

Background: Inherited retinal diseases (IRDs) are a leading cause of blindness in children and working age adults in the United Kingdom and other countries, with an appreciable socioeconomic impact. However, by definition, IRD data are individually rare, and as a result, this patient group has been underserved by research. Researchers need larger amounts of these rare data to make progress in this field, for example, through the development of gene therapies. The challenge has been how to find and make these data available to researchers in the most productive way. MyEyeSite is a research collaboration aiming to design and develop a digital platform (the MyEyeSite platform) for people with rare IRDs that will enable patients, doctors, and researchers to aggregate and share specialist eye health data. A crucial component of this platform is the MyEyeSite patient application, which will provide the means for patients with IRD to interact with the system and, in particular, to collate, manage, and share their personal specialist IRD data both for research and their own health care. / Objective: This study aims to test the acceptability and feasibility of the MyEyeSite platform in the target IRD population through a collaborative patient-centered study. / Methods: Qualitative data were generated through focus groups and workshops, and quantitative data were obtained through a survey of patients with IRD. Participants were recruited through clinics at Moorfields Eye Hospital National Health Service (NHS) Foundation Trust and the National Institute for Health Research (NIHR) Moorfields Biomedical Research Centre through their patient and public involvement databases. / Results: Our IRD focus group sample (n=50) highlighted the following themes: frustration with the current system regarding data sharing within the United Kingdom’s NHS; positive expectations of the potential benefits of the MyEyeSite patient application, resulting from increased access to this specialized data; and concerns regarding data security, including potentially unethical use of the data outside the NHS. Of the surveyed 80 participants, 68 (85%) were motivated to have a more active role in their eye care and share their data for research purposes using a secure technology, such as a web application or mobile app. / Conclusions: This study demonstrates that patients with IRD are highly motivated to be actively involved in managing their own data for research and their own eye care. It demonstrates the feasibility of involving patients with IRD in the detailed design of the MyEyeSite platform exemplar, with input from the patient with IRD workshops playing a key role in determining both the functionality and accessibility of the designs and prototypes. The development of a user-centered technological solution to the problem of rare health data has the potential to benefit not only the patient with IRD community but also others with rare diseases

Can artificial intelligence accelerate the diagnosis of inherited retinal diseases? Protocol for a data-only retrospective cohort study (Eye2Gene)

INTRODUCTION: Inherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over 300 genes have been found to be associated with IRDs and identifying the affected gene in patients by molecular genetic testing is the first step towards effective care and patient management. However, genetic diagnosis is currently slow, expensive and not widely accessible. The aim of the current project is to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service. METHODS AND ANALYSIS: The data-only retrospective cohort study involves a target sample size of 10 000 participants, which has been derived based on the number of participants with IRD at three leading UK eye hospitals: Moorfields Eye Hospital (MEH), Oxford University Hospital (OUH) and Liverpool University Hospital (LUH), as well as a Japanese hospital, the Tokyo Medical Centre (TMC). Eye2Gene aims to predict causative genes from retinal images of patients with a diagnosis of IRD. For this purpose, 36 most common causative IRD genes have been selected to develop a training dataset for the software to have enough examples for training and validation for detection of each gene. The Eye2Gene algorithm is composed of multiple deep convolutional neural networks, which will be trained on MEH IRD datasets, and externally validated on OUH, LUH and TMC. ETHICS AND DISSEMINATION: This research was approved by the IRB and the UK Health Research Authority (Research Ethics Committee reference 22/WA/0049) 'Eye2Gene: accelerating the diagnosis of IRDs' Integrated Research Application System (IRAS) project ID: 242050. All research adhered to the tenets of the Declaration of Helsinki. Findings will be reported in an open-access format

Can artificial intelligence accelerate the diagnosis of inherited retinal diseases? Protocol for a data-only retrospective cohort study (Eye2Gene)

Introduction Inherited retinal diseases (IRD) are a leading cause of visual impairment and blindness in the working age population. Mutations in over 300 genes have been found to be associated with IRDs and identifying the affected gene in patients by molecular genetic testing is the first step towards effective care and patient management. However, genetic diagnosis is currently slow, expensive and not widely accessible. The aim of the current project is to address the evidence gap in IRD diagnosis with an AI algorithm, Eye2Gene, to accelerate and democratise the IRD diagnosis service. Methods and analysis The data-only retrospective cohort study involves a target sample size of 10 000 participants, which has been derived based on the number of participants with IRD at three leading UK eye hospitals: Moorfields Eye Hospital (MEH), Oxford University Hospital (OUH) and Liverpool University Hospital (LUH), as well as a Japanese hospital, the Tokyo Medical Centre (TMC). Eye2Gene aims to predict causative genes from retinal images of patients with a diagnosis of IRD. For this purpose, 36 most common causative IRD genes have been selected to develop a training dataset for the software to have enough examples for training and validation for detection of each gene. The Eye2Gene algorithm is composed of multiple deep convolutional neural networks, which will be trained on MEH IRD datasets, and externally validated on OUH, LUH and TMC. Ethics and dissemination This research was approved by the IRB and the UK Health Research Authority (Research Ethics Committee reference 22/WA/0049) ‘Eye2Gene: accelerating the diagnosis of IRDs’ Integrated Research Application System (IRAS) project ID: 242050. All research adhered to the tenets of the Declaration of Helsinki. Findings will be reported in an open-access format

Constraining globular cluster formation through studies of young massive clusters - V. ALMA observations of clusters in the Antennae

Some formation scenarios that have been put forward to explain multiple populations within Globular Clusters (GCs) require that the young massive cluster have large reservoirs of cold gas within them, which is necessary to form future generations of stars. In this paper we use deep observations taken with Atacama Large Millimeter/sub-millimeter Array (ALMA) to assess the amount of molecular gas within 3 young (50 − 200 Myr) massive (� 106 M⊙) clusters in the Antennae galaxies. No significant CO(3–2) emission was found associated with any of the three clusters. We place upper limits for the molecular gas within these clusters of � 1 × 105 M⊙ (or < 9% of the current stellar mass). We briefly review different scenarios that propose multiple episodes of star formation and discuss some of their assumptions and implications. Our results are in tension with the predictions of GC formation scenarios that expect large reservoirs of cool gas within young massive clusters at these ages

Star clusters near and far; tracing star formation across cosmic time

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00690-x.Star clusters are fundamental units of stellar feedback and unique tracers of their host galactic properties. In this review, we will first focus on their constituents, i.e.\ detailed insight into their stellar populations and their surrounding ionised, warm, neutral, and molecular gas. We, then, move beyond the Local Group to review star cluster populations at various evolutionary stages, and in diverse galactic environmental conditions accessible in the local Universe. At high redshift, where conditions for cluster formation and evolution are more extreme, we are only able to observe the integrated light of a handful of objects that we believe will become globular clusters. We therefore discuss how numerical and analytical methods, informed by the observed properties of cluster populations in the local Universe, are used to develop sophisticated simulations potentially capable of disentangling the genetic map of galaxy formation and assembly that is carried by globular cluster populations.Peer reviewedFinal Accepted Versio

The Physics of Star Cluster Formation and Evolution

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00689-4.Star clusters form in dense, hierarchically collapsing gas clouds. Bulk kinetic energy is transformed to turbulence with stars forming from cores fed by filaments. In the most compact regions, stellar feedback is least effective in removing the gas and stars may form very efficiently. These are also the regions where, in high-mass clusters, ejecta from some kind of high-mass stars are effectively captured during the formation phase of some of the low mass stars and effectively channeled into the latter to form multiple populations. Star formation epochs in star clusters are generally set by gas flows that determine the abundance of gas in the cluster. We argue that there is likely only one star formation epoch after which clusters remain essentially clear of gas by cluster winds. Collisional dynamics is important in this phase leading to core collapse, expansion and eventual dispersion of every cluster. We review recent developments in the field with a focus on theoretical work.Peer reviewe

Probing the Dragonfish star-forming complex: the ionizing population of the young massive cluster Mercer 30

It has recently been claimed that the nebula, Dragonfish, is powered by a superluminous but elusive OB association. However, systematic searches in near-infrared photometric surveys have found many other cluster candidates in this region of the sky. Among these, the first confirmed young massive cluster was Mercer 30, where Wolf-Rayet stars were found.We perform a new characterization of Mercer 30 with unprecedented accuracy, combining NICMOS/HST and VVV photometric data with multi-epoch ISAAC/VLT H- and K-band spectra. Stellar parameters for most of spectroscopically observed cluster members are found through precise non-LTE atmosphere modeling with the CMFGEN code. Our spectrophotometric study for this cluster yields a new, revised distance of d = (12.4 ± 1.7) kpc and a total of QHMc30 ≈ 6.70 × 1050 s-1 Lyman ionizing photons. A cluster age of (4.0 ± 0.8) Myr is found through isochrone fitting, and a total mass of (1.6 ± 0.6) × 104M⊙ is estimated, thanks to our extensive knowledge of the post-main-sequence population. As a consequence, membership of Mercer 30 to the Dragonfish star-forming complex is confirmed, allowing us to use this cluster as a probe for the whole complex, which turns out to be extremely large (~400 pc across) and located at the outer edge of the Sagittarius-Carina spiral arm (~11 kpc from the Galactic center). The Dragonfish complex hosts 19 young clusters or cluster candidates (including Mercer 30 and a new candidate presented in this work) and an estimated minimum of nine field Wolf-Rayet stars. All these contributions account for, at least 73% of the ionization of the Dragonfish nebula and leaves little or no room for the alleged superluminous OB association; alternative explanations are discussed